According to the Hurun Global Rich List 2025, the city with the highest number of billionaires in 2025 was New York. In detail, *** billionaires resided in the American city. Furthermore, ** billionaires lived in London, while Shanghai had a billionaire population of ** individuals. New York was the only city in the world with more than 100 billionaires that year. Mega-cities of the world A large number of the world’s billionaires are concentrated in a select number of the world’s megacities. This has as much to do with the location of their wealth, business interests, and further earning potential as it does with the quality of life in those cities. A look at the most significant industries in the global billionaire production line helps to explain the prominence of the traditional capitals of global business, including New York, London, and Hong Kong. The place of many Chinese cities on the list can in part be explained by the strong performance of industrial conglomerates from the country recently. Economic growth in China While New York is the city with the highest number of billionaires, China now boasts the most billionaires of any country in the world. However, ***** of the top ten wealthiest billionaires still came from the United States as of 2025.

This statistic shows the top 5 African cities in 2014 by number of residing billionaires. In 2014, ** billionaires were living in Lagos, Nigeria.

Cleaned dataset from the Billionaires Statistic Dataset (2023) that can be found here.

The code I used to clean and re-structure the data is also here.

First things first: a big shout-out to Nidula Elgiriyewithana for providing the original data.

As with it, this dataset contains various information about the world's wealthiest persons in different columns that can be grouped into three different types:

• Business-related information. These columns contain data about the industry in which the billionaires' operate, their source of wealth, total wealth and position they occupy in the ranking.
• Personal information. Such as name, age, nationality, country and city of residence.
• Economic activity information. These columns are related to the country in which the billionaire resides and provide different economic indicators like GDP, education enrollment or Consumer Price Index (CPI).

Column names

• position. Ranking of the billionaire measured by their wealth.
• wealth. The wealth of the billionaire measured in $.
• industry. Industry in which the billionaire's operates their businesses.
• full_name. Complete name of the billionaire.
• age. The age of the billionaire.
• country_of_residence. Country in which the billionaire resides.
• city_of_residence. City in which the billionaire resides.
• source. The source of the billionaire's wealth.
• citizenship. The country of citizenship of the billionaire.
• gender. The gender of the billionaire.
• birth_date. The birth date of the billionaire.
• last_name. The last name of the billionaire.
• first_name. The first name of the billionaire.
• residence_state. State in which the billionaire resides (only for billionaires who reside in the U.S.).
• residence_region. Region in which the billionaire resides (only for billionaires who reside in the U.S.).
• birth_year. The birth year of the billionaire.
• birth_month. The birth month of the billionaire.
• birth_day. The birth data of the billionaire.
• cpi_country. Consumer Price Index (CPI) for the billionaire's country.
• cpi_change_country. CPI change for the billionaire's country.
• gdp_country. Gross Domestic Product (GDP) in $ for the billionaire's country.
• g_tertiary_ed_enroll. Enrollment in tertiary education in the billionaire's country.
• g_primary_ed_enroll. Enrollment in primary education in the billionaire's country.
• life_expectancy. Life expectancy in the billionaire's country.
• tax_revenue. Tax revenue in the billionaire's country.
• tax_rate. Total tax rate in the billionaire's country.
• country_pop. Population of the billionaire's country.
• country_lat. Latitude coordinate of the billionaire's country.
• country_long. Longitude coordinate of the billionaire's country.
• continent. Continent in which the country of the billionaire's residence is located.

Potential analyses

• Analyze which industries contain the biggest groups of billionaires overall and in different countries.
• Explore number of billionaires and total wealth across countries and continents and display the result in a map.
• Focus on personal information columns such as age or gender to explore the distribution of billionaires from this perspective.
• Discover if countries' economic indicators have any impact in the presence of billionaires.
• The U.S. is the country with most billionaires presented in the dataset and also the only one with attributes in the residence_state and residence_region columns. This makes the American billionaires a good focus for a specific analysis.

Bonus

If you want a challenge, you can create a dashboard using tools such as Plotly to dynamically visualize the data using one or different attributes (such as industry, age or country). I did it, leave the link below in case you want to investigate:

Dashboard notebook here

If you find this dataset informative or inspirational, a vote is appreciated for others to easily discover value in it 💎💰

This statistic illustrates the number of billionaires in leading cities in the EMEA (Europe, the Middle East and Asia) region as of 2016. It can be seen that the number of billionaires in Moscow stood at a total of **, making Moscow the city in the EMEA region with the most billionaires at that time. Although this is the case London was not far behind, ranking second with a total of ** billionaires as of 2016.

In January 2024, approximately ******* hoseholds in Beijing owned assets worth *********** yuan ore more. Beijing, Shanghai, and Hong Kong were home to by far the highest number of millionaires in Greater China.

Introduction: The "Forbes Billionaires Evolution" dataset provides a comprehensive examination of the financial growth and status of global billionaires from 1997 to 2024. It meticulously chronicles the transformations, both subtle and substantial, in the fortunes of these financial titans over nearly three decades.

The cover image used for this dataset is sourced from Forbes, with the illustration credited to Geoff J. Kim for Forbes.

Content: This dataset offers a plethora of valuable information, including: - Yearly rankings. - Net worth details and evolution. - Personal details like names, age, gender, and birth dates. - Residence details spanning country, city, and citizenship. - In-depth business category and industry classifications. - Details about affiliations with various organizations, including positions held. - Indicators like "self-made" and the current wealth status.

Use Cases: The potential applications for this dataset are vast and varied: 1. Financial Analysis: Understand the wealth patterns and trajectories of the world's richest individuals. 2. Sociological Studies: Examine the dynamics of wealth in relation to factors like age, gender, and nationality. 3. Business Strategy: Identify industries and regions with the most billionaire activity and growth. 4. Academic Research: Serve as a foundational resource for theses, dissertations, or coursework related to finance, business, or socio-economics. 5. Journalism: Craft compelling stories around the ascent or decline of billionaires in different epochs.

Leverage this dataset to extract trends, narratives, and crucial data-driven insights into the financial landscape of our world's most affluent individuals.

In 2022, ****** was home to the highest number of millionaires, followed by India’s capital New Delhi, and the IT capital - Bengaluru. This comes as no surprise since all three cities have the largest share of high net worth households along with a booming economic outlook. Overall, India had around *** billionaires as of March 2023, and ranked third globally in terms of its ultra-net-worth individuals. A growing wealth gap Despite this, India also has a very high wealth inequality with millions of people living below the poverty line. In fact, according to the last census, the state of Maharashtra (with Mumbai as its capital city) had the highest number of slums across the country with over *** million households. Furthermore, according to a 2015 study on the geography of the super-rich, Bangalore was ranked first in terms of the inequality between its rich and poor, with the wealth of the city’s billionaires being ******* times that of the average per capita GDP in the city. Mumbai came second in this listing, while Delhi was ranked fifth. It's a rich man's world As of 2018, the richest ** percent of Indians owned **** percent of the country’s wealth. The Indian economy was also seen to be one of the fastest growing economies across the world. This indicates the level of unequal distribution of wealth in the country. This is a matter of grave concern and has several implications in terms of the country’s development and progress.

Certainly! Here's a description of each column:

Rank: The numerical ranking of a person or entity in a list or category.

finalWorth: The final worth or net worth of a person or entity, typically in terms of monetary value.

category: The category or classification of a person or entity, such as "entrepreneur", "investor", "celebrity", etc.

personName: The name of a person.

age: The age of a person.

country: The country of residence or origin of a person or entity.

city: The city of residence or origin of a person or entity.

source: The source or origin of wealth or fame for a person or entity.

industries: The industries or sectors in which a person or entity operates or is associated with.

countryOfCitizenship: The country of citizenship of a person.

organization: The organization or company with which a person is associated.

selfMade: Indicates whether a person is self-made or inherited wealth/fame.

**status: **The status or position of a person or entity, such as "CEO", "founder", "chairman", etc.

gender: The gender of a person.

**birthDate: **The date of birth of a person.

lastName: The last name or surname of a person.

**firstName: **The first name of a person.

title: The title or honorific used for a person, such as "Mr.", "Mrs.", "Dr.", etc.

date: The date associated with a particular event or data entry.

**state: **The state or region of residence or origin of a person or entity.

residenceStateRegion: The state or region of residence of a person or entity.

birthYear: The year of birth of a person.

birthMonth: The month of birth of a person.

**birthDay: **The day of birth of a person.

**cpi_country: **Consumer Price Index (CPI) for a specific country.

cpi_change_country: Change in Consumer Price Index (CPI) for a specific country.

**gdp_country: **Gross Domestic Product (GDP) for a specific country.

**gross_tertiary_education_enrollment: **Gross tertiary education enrollment rate for a specific country.

gross_primary_education_enrollment_country: Gross primary education enrollment rate for a specific country.

**life_expectancy_country: **Life expectancy for a specific country.

tax_revenue_country_country: Tax revenue for a specific country.

**total_tax_rate_country: **Total tax rate for a specific country.

population_country: Population of a specific country.

**latitude_country: **Latitude coordinates of a specific country.

**longitude_country: **Longitude coordinates of a specific country.

These columns appear to contain various attributes and metrics related to individuals, countries, and economic indicators.

According to the Hurun Global Rich List 2025, the United States housed the highest number of billionaires worldwide in 2025. In detail, there were *** billionaires living in the United States as of January that year. By comparison, *** billionaires resided in China. India, the United Kingdom, and Germany were also the homes of a significant number of billionaires that year. United States has regained its first place As the founder and exporter of consumer capitalism, it is no surprise that the United States is home to a large number of billionaires. Although China had briefly overtaken the U.S. recently, the United States has reclaimed its position as the country with the most billionaires in the world. Moreover, North America leads the way in terms of the highest number of ultra high net worth individuals – those with a net worth of more than ***** million U.S. dollars. The prominence of Europe and North America is a reflection of the higher degree of economic development in those states. However, this may also change as China and other emerging economies continue developing. Female billionaires Moreover, the small proportion of female billionaires does little to counter critics claiming the global economy is dominated by an elite comprised mainly of men. On the list of the richest people in the world, only *** were women. Moreover, recent political discourse has put a great amount of attention on the wealth held by the super-rich, with the wealth distribution of the global population being heavily unequal.

This comprehensive dataset encapsulates a detailed snapshot of the wealthiest individuals globally, as listed by Forbes in 2024. Compiled through meticulous web scraping and data aggregation, the dataset includes a wide range of attributes for each billionaire. Fields encompass basic personal information such as name, age, and gender, alongside financial details including net worth and sources of wealth. The dataset further delves into aspects like industry involvement, organizational affiliations, philanthropic endeavors, and educational backgrounds.

Key attributes in this dataset include:

Name: Full legal name of the billionaire. Age: Age of the individual. 2024 Net Worth: Estimated net worth in USD for the year 2024. Industry: Primary industry or sector of operation. Source of Wealth: Origin of the billionaire’s wealth. Title: Professional title or position. Organization: Name of the associated organization. Self-Made: Indicator if the wealth is self-made. Self-Made Score: A quantitative score assessing how self-made their wealth is. Philanthropy Score: A score reflecting the extent of their philanthropic activities. Residence: Main residence of the individual. Citizenship: Legal citizenship. Gender: Gender identity. Marital Status: Current marital status. Children: Number of children. Education: Highest level of education attained.

This dataset is ideal for analysis, offering insights into the distribution of wealth, the influence of education on wealth accumulation, and trends across different industries. It also provides a foundation for exploring the impact of socioeconomic factors on personal wealth. The data were collected and formatted with careful consideration to ensure accuracy, making it a valuable resource for researchers, economists, and anyone interested in the dynamics of wealth and success.

Please note that some data is missing in this dataset, primarily due to the unavailability of information from Forbes. This issue becomes more prevalent beyond the top 400 entries. Many individuals lack a self-made score, a philanthropy score, or specific details regarding their title or organization as per Forbes' listings. I am currently working to update the dataset with this missing information. However, this update process is quite tedious and time-consuming since it is mostly manual. I appreciate your patience and understanding as I work through these details.

Content

This dataset consists of top most billionaires in the world and respective their names, whether it is a finance company or any software company, how much money they have ,these all the details which are in the dataset

Researchers have compiled a multi-decade database of the super-rich. Building off the Forbes World’s Billionaires lists from 1996-2014, scholars at Peterson Institute for International Economics have added a couple dozen more variables about each billionaire - including whether they were self-made or inherited their wealth. (Roughly half of European billionaires and one-third of U.S. billionaires got a significant financial boost from family, the authors estimate.)

Acknowledgements

Reference : https://corgis-edu.github.io/corgis/csv/billionaires/

Inspiration

Some of the datasets which I have seen in the kaggle or somewhere but it is limited to less number of columns . Kagglers are not able to get an insights from very low amount of data. so that I decided that to be more helpful to them or we can able to get an more insights from this dataset

A dataset listing the 20 richest cities in Montana for 2024, including information on rank, city, county, population, average income, and median income.

Forbes has been regularly publishing and maintaining a list of billionaires around the world on its website : https://www.forbes.com/billionaires/

But Forbes do not provide historical data about the billionaires and their position in time.

There are two different datasets first is 'forbes billionaire list' which is obtained from wayback machine by web scraping the forbes's website's yearly snapshots. The second dataset is 'countries with billionaires' which is built upon the first dataset and grouped by countries and the number of billionaires it has.

As of March 2024, California was the U.S. state with most billionaires, with *** billionaires calling the state home. New York was second, with *** resident billionaires.

1) Data Introduction • The Billionaires Statistics Dataset (2023) is a comprehensive set of personal and business information, including rankings of billionaires worldwide, net assets, industries, businesses, nationalities, birth and residence information, and asset sources.

2) Data Utilization (1) Billionaires Statistics Dataset (2023) has characteristics that: • The dataset consists of more than 35 columns, including the billionaire's rank, final Worth, industry, country, age, country of residence, source of assets, related industries, citizenship, organization, selfMade, birth information, data collection date, economic and social indicators (GDP, CPI, education enrollment, life expectancy, tax revenue, population, etc.). • In addition to individual asset information, economic indicators and demographic data by country are combined, allowing a three-dimensional analysis of billionaires and each country's economic and social environment. (2) Billionaires Statistics Dataset (2023) can be used to: • Wealth Distribution and Industry Analysis: Using billionaires' net worth, industry, and national data, we can analyze global wealth concentration and wealth distribution by industry and region. • A study linking demographics and economic indicators: Billionaire data can be combined with various economic and social indicators such as GDP, CPI, tax revenue, education, and life expectancy to be used for in-depth research on wealth formation, social background, ratio of self-made and inherited wealth, and regional characteristics.

📲 New Update ⏳

Two new additional features are added, "**Industry**": which industry they are working on? "Is it manufacturing, Technology, Fashion, Retail etc." and their "**Age**"

People richer than poor people (Check out the discussion forum for popularity, peace and peaceful protest and a sudden UPRISING 😂 😆 )

This Dataset contains list of all the people categorized as Billionaires of 2021 by Forbes in their 35th Annual World's Billionaires List.

What They have that we don't (Of course Money)

p.s- If you think its money only, just a "HAHAHA :)" for you

Cutting all the dank vibes, let's get serious now! This Dataset contains "Name of each Billionaire", "Country: They are based on!", "Source of their Income/ Company Name", "Their net worth that makes them richer than POOR PEOPLE " and "Their global position in terms of their net worth", "Industry": which industry they are working on? and their "Age".

Acknowledgements

Thanks to Python and Web Scraping and of course Forbes Real Time Billionaires list

Inspiration

Lets predict in the upcoming years which countries will have the maximum number of billionaires in the world.

This article introduces an original dataset of formal political participation for over 2,000 individuals included in the Forbes Billionaires List. We find that billionaire politicians are a surprisingly common phenomenon: Over 11% of the world’s billionaires have held or sought political office. Even compared to other elite groups known for producing politicians from their ranks, this is a high rate of political participation. Moreover, billionaires focus their political ambitions on influential positions, have a strong track record of winning elections, and lean to the right ideologically. We also document substantial cross-national variation: A country’s number of billionaire politicians is not simply a product of its total number of billionaires but is instead related to regime type. Indeed, billionaires formally enter the political sphere at a much higher rate in autocracies than in democracies. We conclude by discussing the normative implications of our findings and outlining a new research agenda on billionaire politicians.

Dataset

This dataset was created by Mohamed Fawzy Hassan

Released under Other (specified in description)

Contents

This dataset provides a synthetic overview of the 1,000 wealthiest individuals in the world, offering insights into the distribution of wealth across industries and regions. It is designed to help analysts, researchers, and data enthusiasts explore global wealth trends, industry dominance, and regional wealth concentration.

Whether you're conducting market research, financial analysis, or data modeling, this dataset serves as a valuable resource for understanding the characteristics of the world's top billionaires.

📊 Key Features: Name 👤: The name of the billionaire. Country 🌍: Country of residence or primary business operation. Industry 🏭: Industry in which the individual has built their wealth. Net Worth (in billions) 💵: Estimated net worth in billions of USD. Company 🏢: The primary company or business associated with the billionaire. ⚠️ Important Note: This dataset is 100% synthetic and does not contain real financial or personal data. It is artificially generated for educational, analytical, and research purposes.

The highest number of billionaires in 2023 was found in North America, reaching over 1,100. They were closely followed by Europe and Asia, whereas the gap down to the other regions of the world was significant.